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dc.contributor.authorSchmitt, Thilo A.-
dc.contributor.authorSchäfer, Rudi-
dc.contributor.authorDette, Holger-
dc.contributor.authorGuhr, Thomas-
dc.date.accessioned2014-08-08T07:20:59Z-
dc.date.available2014-08-08T07:20:59Z-
dc.date.issued2014-08-08-
dc.identifier.urihttp://hdl.handle.net/2003/33565-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-6675-
dc.description.abstractWe conduct an empirical study using the quantile-based correlation function to uncover the temporal dependencies in financial time series. The study uses intraday data for the S&P 500 stocks from the New York Stock Exchange. After establishing an empirical overview we compare the quantile-based correlation function to stochastic processes from the GARCH family and find striking differences. This motivates us to propose the quantile-based correlation function as a powerful tool to assess the agreements between stochastic processes and empirical data.en
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB 823;28/2014en
dc.subjecttime seriesen
dc.subjectstochastic processen
dc.subjectempirical dataen
dc.subject.ddc310-
dc.subject.ddc330-
dc.subject.ddc620-
dc.titleQuantile correlations: Uncovering temporal dependencies in financial time seriesen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 823

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